I det här arbetet har jag undersökt melodiernas kvalitet och vilka byggstenar som ligger till grund för melodins intresse. Därför begränsade jag mig till att skriva sex ”four chords”-låtar där jag sedan bedömde och analyserade resultatet. Jag kom fram till att melodins samverkan med rytmen samt användandet av pauser är av största vikt för att melodin ska finna mitt intresse.

Background: In recent years, the emerging electronic cigarette (e-cigarette) marketplace has developed prosperously all over the world. By analyzing online e-liquid reviews, we seek to identify the features attracting users. Methods: We collected e-liquid reviews from one of the largest online e-liquid review websites and extracted the e-liquid features by keywords. Then we used sentiment analysis to classify the features into two polarities: positive and negative. The positive sentiment ratio of a feature reflects the e-cigarette users' preference on this feature. Results: The popularity and preference of e-liquid features are not correlated. Nuts and cream are the favorite flavor categories, while fruit and cream are the most popular categories. The top mixed flavors are preferable to single flavors. Fruit and cream categories are most frequently mixed with other flavors. E-cigarette users are satisfied with cloud production, but not satisfied with the ingredients and throat hit. Conclusions: We identified the flavors that e-cigarette users were satisfied with, and we found the users liked e-cigarette cloud production. Therefore, flavors and cloud production are potential factors attracting new users.

Sverige är ett av de mest framträdande digitaliserade länderna inom EU. Men vissa sektorer har hamnat efter i digitaliseringsprocessen, en av dem är sjukvården. Sjukvården är en av de mest informationsintensiva sektorerna i det svenska samhället, det är kritiskt att IT-systemen är sammanhållna och kommunicerande med varandra, s.k. interoperabla. Just där brister sjukvårdens IT-system idag, men sjukvården som organisation brister också i att ha någon form av enhetlig standard för hur vårdinformation ska dokumenteras. Dessa brister leder till försämrad vårdkvalitet och arbetsmiljö för vårdpersonalen. Syftet med denna studie är att utveckla en artefakt för hur blockkedjeteknikens egenskaper kan användas för att förbättra interoperabiliteten i de svenska hälso- och sjukvårdssystemen. Vi har genomfört studien med en designbaserad metod, där vi tar fram en modell baserat på blockkedjans egenskaper och presenterade problem utifrån sex intervjuer av personer som arbetar med IT i vården. Vårt resultat visar att blockkedjan har egenskaper som kan stödja interoperabilitet i sjukvården. Resultatet visar också det krävs en balans mellan säkerhet och flexibilitet samt någon form av standard för hur vårdinformation ska dokumenteras, antingen på nationell eller regional nivå, för att skapa interoperabilitet. / Sweden is one of the most prominent digitized countries within the European Union. But some sectors have fallen behind in the digitizing process; one of them is the healthcare sector. The healthcare sector is one of the most information intensive fields in the Swedish society, where it is critical that the IT-systems are integrated and communicative with each other, so-called interoperable. Today's IT systems in healthcare are failing in terms of interoperability, but the healthcare itself as an organisation also fails to have some sort of uniform standard for documenting health data. These deficiencies lead to an impaired quality of care for the patients but also a worsened environment for the healthcare professionals. The purpose of this study is to develop an artefact for how the capabilities of the blockchain technology can be used to improve interoperability within the Swedish healthcare systems. We’ve conducted this paper by using a design-science based method, where we have developed a model based on the capabilities of blockchain technology and issues presented based on interviews with six people working with IT within healthcare. Our findings show that the blockchain technology has capabilities that can support interoperability within the healthcare systems. Our findings also show that to achieve interoperability there is a need to balance security and flexibility as well as some form of unified standard for how healthcare data is to be documented, on either a national or regional level.

The health care industry is transforming into an industry that requires health information technology, yet many health care organizations are reluctant to implement new technology. The purpose of this case study was to explore strategies that led to a successful transition from an older electronic health record (EHR) system to a compliant EHR system at a multisite hospital system (MHS). The study included face-to-face and phone interviews with 12 managers who worked on the transition of an MHS's EHR system in the Pacific Northwest region of the United States. The technology acceptance model was used to frame the study. Audio recordings with these managers were transcribed and analyzed along with interview notes and publicly available documents to identify themes regarding strategies used by managers to successfully upgrade to a compliant EHR system at an MHS. Three major themes emerged: hybrid implementation strategy, training strategy, and social pressure strategy. Results may be used to facilitate the adoption of information technology systems in any industry. Results may directly benefit other MHSs by facilitating successful EHR system transitions. Implications for social change include improved care coordination, reductions in duplicated medical procedures, and more timely and relevant tests for patients through the full use of EHRs.

Deep Learning (DL) has been broadly applied to solve big data problems in biomedical fields, which is most successful in image processing. Recently, many DL methods have been applied to analyze genomic studies. However, genomic data usually has too small a sample size to fit a complex network. They do not have common structural patterns like images to utilize pre-trained networks or take advantage of convolution layers. The concern of overusing DL methods motivates us to evaluate DL methods' performance versus popular non-deep Machine Learning (ML) methods for analyzing genomic data with a wide range of sample sizes. In this paper, we conduct a benchmark study using the UK Biobank data and its many random subsets with different sample sizes. The original UK Biobank data has about 500k participants. Each patient has comprehensive patient characteristics, disease histories, and genomic information, i.e., the genotypes of millions of Single-Nucleotide Polymorphism (SNPs). We are interested in predicting the risk of three lung diseases: asthma, COPD, and lung cancer. There are 205,238 participants have recorded disease outcomes for these three diseases. Five prediction models are investigated in this benchmark study, including three non-deep machine learning methods (Elastic Net, XGBoost, and SVM) and two deep learning methods (DNN and LSTM). Besides the most popular performance metrics, such as the F1-score, we promote the hit curve, a visual tool to describe the performance of predicting rare events. We discovered that DL methods frequently fail to outperform non-deep ML in analyzing genomic data, even in large datasets with over 200k samples. The experiment results suggest not overusing DL methods in genomic studies, even with biobank-level sample sizes. The performance differences between DL and non-deep ML decrease as the sample size of data increases. This suggests when the sample size of data is significant, further increasing sample sizes leads to more performance gain in DL methods. Hence, DL methods could be better if we analyze genomic data bigger than this study. / Graduate

No description available.

No description available.

Background: Heparin-induced thrombocytopenia (HIT) is an adverse drug reaction characterized by a lowered platelet count (50% from baseline) 4-10 days after heparin exposure. Autoantibodies specific for platelet factor 4 (PF4) bind PF4 and heparin complexes (PF4/H) and activate platelets through the FcgammaRIIA receptor. Severe cases of HIT can result in thrombotic complications including deep vein thrombosis, pulmonary embolism, and death. Pathogenic class-switched antibodies against PF4/H (IgG) are detectable in circulation as early as five days post-heparin exposure and peak at 14 days. The timeline and class of antibody found in HIT patients suggest that there must be pre-existing immunity against PF4/H. Thus, B cells producing anti-PF4/H antibodies must exist prior to heparin exposure. Cardiac surgery patients are disproportionately prone to anti-PF4/H seroconversion (up to 70%) and thus are utilized in this study as a model patient group. Research objective: The objective of this study is to determine whether the preoperative immune profile is associated with postoperative anti-PF4/H antibody production in a cohort of patients undergoing cardiac pulmonary bypass (CPB) surgery. Materials and methods: To characterize the preoperative immune profile, we used 1) a peripheral blood mononuclear cell (PBMC) enzyme linked immunospot (ELISPOT) assay to measure the prevalence of preoperative anti-PF4/H specific antibody secreting cells (ASC) and 2) a PF4/H-dependant enzyme immunoassay (EIA) to measure the anti-PF4/H antibodies produced by PBMCs in vitro. To characterize postoperative anti-PF4/H seroconversion in CPB patients, we used a PF4/H dependent EIA to measure in vivo levels of anti-PF4/H antibodies produced postoperatively. We also utilize a functional assay, 14C-serotonin release assay (SRA) to determine if seroconverting patients produced platelet activating antibody. Results: All patients were able to produce anti-PF4/H spots in the ELISPOT; however, this did not correlate with the titer of antibody production in vitro nor did it correlate with antibody production in the postoperative period. Instead, we found that pre-operative in vitro anti-PF4/H IgM production was associated with post-operative IgG anti-PF4/H seroconversion (Spearman’s r=0.39, P=0.018). We observed that 92.1% of CPB patients produced PF4/H antibody at postoperative week 3 with some combination of IgA, IgG, and IgM. Of the anti-PF4/H seropositive patients, 26% developed platelet activating antibody and were found seropositive when the SRA was supplemented with PF4 instead of heparin, while 15.7% were seropositive in the original SRA. It was noted that 4 of 10 patients that caused the most robust platelet activation were also seropositive for anti-PF4/H IgA antibody. Lastly, throughout this serosurveillance study, several patients that demonstrated unique immunological features are presented in this study as case studies. Specifically, we report the preoperative, surgical, clinical and postoperative characteristics for 3 patients of interest: 1) in a preoperative setting, a CPB patient’s PBMC were able to be activated and produce anti-PF4/H IgG antibody in vitro, 2) the second patient had platelet-activating antibodies in circulation prior to intraoperative heparin challenge and early post-surgery 3) the third patient who developed probable HIT. Conclusions: Based on our findings, we conclude that preoperative PF4/H ELISPOTs were unable to predict post-operative production of anti PF4/H antibodies. However, preoperative in vitro production of anti-PF4/H IgM may be associated with postoperative production of anti-PF4/IgG antibody and should be investigated further as this may help to elucidate the mechanisms for anti-PF4/H production related to HIT. / Thesis / Master of Science (MSc)

Résumé : La détection des bâtiments dans les images à très haute résolution spatiale (THRS) a plusieurs applications pratiques et représente un domaine de recherche scientifique intensive ces dernières années. Elle fait face à la complexité du milieu urbain et aux spécificités des images provenant des différents capteurs. La performance des méthodes existantes pour l’extraction des bâtiments n’est pas encore suffisante pour qu’elles soient généralisées à grande échelle (différents types de tissus urbains et capteurs). Les opérateurs morphologiques se sont montrés efficaces pour la détection des bâtiments dans les images panchromatiques (images en niveaux de gris) à très haute résolution spectrale (THRS). L’information spectrale issue des images multispectrales est jugée nécessaire pour l’amélioration de leur performance. L’extension des opérateurs morphologiques pour les images multispectrales exige l’adoption d’une stratégie qui permet le traitement des pixels sous forme de vecteurs, dont les composantes sont les valeurs dans les différentes bandes spectrales. Ce travail de recherche vise l’application de la transformation morphologique dite Hit-or-Miss (HMT) à des images multispectrales à THRS, afin de détecter des bâtiments. Pour répondre à la problématique de l’extension des opérateurs morphologiques pour les images multispectrales, nous proposons deux solutions. Comme une première solution nous avons généré des images en niveaux de gris à partir les bandes multispectrales. Dans ces nouvelles images les bâtiments potentiels sont rehaussés par rapport à l’arrière-plan. La HMT en niveaux de gris est alors appliquée à ces images afin de détecter les bâtiments. Pour rehausser les bâtiments nous avons proposé un nouvel indice, que nous avons appelé Spectral Similarity Ratio (SSR). Pour éviter de définir des configurations, des ensembles d’éléments structurants (ES), nécessaires pour l’application de la HMT, au préalable, nous avons utilisé l’érosion et la dilatation floues et poursuivi la réponse des pixels aux différentes valeurs des ES. La méthode est testée sur des extraits d’images représentant des quartiers de type résidentiel. Le taux moyen de reconnaissance obtenu pour les deux capteurs Ikonos et GeoEye est de 85 % et de 80 %, respectivement. Le taux moyen de bonne identification, quant à lui, est de 85 % et 84 % pour les images Ikonos et GeoEye, respectivement. Après certaines améliorations, la méthode a été appliquée sur des larges scènes Ikonos et WorldView-2, couvrant différents tissus urbains. Le taux moyen des bâtiments reconnus est de 82 %. Pour sa part, le taux de bonne identification est de 81 %. Dans la deuxième solution, nous adoptons une stratégie vectorielle pour appliquer la HMT directement sur les images multispectrales. La taille des ES de cette transformation morphologique est définie en utilisant la transformation dite chapeau haut-de-forme par reconstruction. Une étape de post-traitement inclut le filtrage de la végétation par l’indice de la végétation NDVI et la validation de la localisation des bâtiments par l’information d’ombre. La méthode est appliquée sur un espace urbain de type résidentiel. Des extraits d’images provenant des capteurs satellitaires Ikonos, GeoEye et WorldView 2 ont été traités. Le taux des bâtiments reconnus est relativement élevé pour tous les extraits - entre 85 % et 97 %. Le taux de bonne identification démontre des résultats entre 74 % et 88 %. Les résultats obtenus nous permettent de conclure que les objectifs de ce travail de recherche, à savoir, la proposition d’une technique pour l’estimation de la similarité spectrale entre les pixels formant le toit d’un bâtiment, l’intégration de l’information multispectrale dans la HMT dans le but de détecter les bâtiments, et la proposition d’une technique qui permet la définition semi-automatique des configurations bâtiment/voisinage dans les images multispectrales, ont été atteints. // Abstract : Detection of buildings in very high spatial resolution images (THRS) has various practical applications and is recently a subject of intensive scientific research. It faces the complexity of the urban environment and the variety of image characteristics depending on the type of the sensor. The performance of existing building extraction methods is not yet sufficient to be generalized to a large scale (different urban patterns and sensors). Morphological operators have been proven effective for the detection of buildings in panchromatic (greyscale) very high spectral resolution (VHSR) images. The spectral information of multispectral images is jugged efficient to improve the results of the detection. The extension of morphological operators to multispectral images is not straightforward. As pixels of multispectral images are pixels vectors the components of which are the intensity values in the different bands, a strategy to order vectors must be adopted. This research thesis focuses on the application of the morphological transformation called Hit-or-Miss (HMT) on multispectral VHSR images in order to detect buildings. To address the issue of the extension of morphological operators to multispectral images we have proposed two solutions. The first one employs generation of greyscale images from multispectral bands, where potential buildings are enhanced. The grayscale HMT is then applied to these images in order to detect buildings. To enhance potential building locations we have proposed the use of Spectral Similarity Ratio (SSR). To avoid the need to set multiple configurations of structuring elements (SE) necessary for the implementation of the HMT, we have used fuzzy erosion and fuzzy dilation and examined the pixel response to different values of SE. The method has been tested on image subsets taken over residential areas. The average rate of recognition for the two sensors, Ikonos and GeoEye, is 85% and 80%, respectively. The average rate of correct identification is 85% and 84%, for Ikonos and GeoEye subsets, respectively. Having made some improvements, we then applied the method to large scenes from Ikonos and WorldView-2 images covering different urban patterns. The average rate of recognized buildings is 82%. The rate of correct identification is 81%. As a second solution, we have proposed a new vector based strategy which allows the multispectral information to be integrated into the percent occupancy HMT (POHMT). Thus, the POHMT has been directly applied on multispectral images. The parameters for the POHMT have been defined using the morphological transformation dubbed top hat by reconstruction. A post-processing step included filtering the vegetation and validating building locations by proximity to shadow. The method has been applied to urban residential areas. Image subsets from Ikonos, GeoEye and WorldView2 have been processed. The rate of recognized buildings is relatively high for all subsets - between 85% and 97%. The rate of correct identification is between 74 % and 88 %. The results allow us to conclude that the objectives of this research, namely, suggesting a technique for estimating the spectral similarity between the pixels forming the roof of a building, the integration of multispectral information in the HMT in order to detect buildings and the proposition of a semiautomatic technique for the definition of the configurations building/neighbourhood in multispectral images, have been achieved.

R??sum?? : La d??tection des b??timents dans les images ?? tr??s haute r??solution spatiale (THRS) a plusieurs applications pratiques et repr??sente un domaine de recherche scientifique intensive ces derni??res ann??es. Elle fait face ?? la complexit?? du milieu urbain et aux sp??cificit??s des images provenant des diff??rents capteurs. La performance des m??thodes existantes pour l???extraction des b??timents n???est pas encore suffisante pour qu???elles soient g??n??ralis??es ?? grande ??chelle (diff??rents types de tissus urbains et capteurs). Les op??rateurs morphologiques se sont montr??s efficaces pour la d??tection des b??timents dans les images panchromatiques (images en niveaux de gris) ?? tr??s haute r??solution spectrale (THRS). L???information spectrale issue des images multispectrales est jug??e n??cessaire pour l???am??lioration de leur performance. L???extension des op??rateurs morphologiques pour les images multispectrales exige l???adoption d???une strat??gie qui permet le traitement des pixels sous forme de vecteurs, dont les composantes sont les valeurs dans les diff??rentes bandes spectrales. Ce travail de recherche vise l???application de la transformation morphologique dite Hit-or-Miss (HMT) ?? des images multispectrales ?? THRS, afin de d??tecter des b??timents. Pour r??pondre ?? la probl??matique de l???extension des op??rateurs morphologiques pour les images multispectrales, nous proposons deux solutions. Comme une premi??re solution nous avons g??n??r?? des images en niveaux de gris ?? partir les bandes multispectrales. Dans ces nouvelles images les b??timents potentiels sont rehauss??s par rapport ?? l???arri??re-plan. La HMT en niveaux de gris est alors appliqu??e ?? ces images afin de d??tecter les b??timents. Pour rehausser les b??timents nous avons propos?? un nouvel indice, que nous avons appel?? Spectral Similarity Ratio (SSR). Pour ??viter de d??finir des configurations, des ensembles d?????l??ments structurants (ES), n??cessaires pour l???application de la HMT, au pr??alable, nous avons utilis?? l?????rosion et la dilatation floues et poursuivi la r??ponse des pixels aux diff??rentes valeurs des ES. La m??thode est test??e sur des extraits d???images repr??sentant des quartiers de type r??sidentiel. Le taux moyen de reconnaissance obtenu pour les deux capteurs Ikonos et GeoEye est de 85 % et de 80 %, respectivement. Le taux moyen de bonne identification, quant ?? lui, est de 85 % et 84 % pour les images Ikonos et GeoEye, respectivement. Apr??s certaines am??liorations, la m??thode a ??t?? appliqu??e sur des larges sc??nes Ikonos et WorldView-2, couvrant diff??rents tissus urbains. Le taux moyen des b??timents reconnus est de 82 %. Pour sa part, le taux de bonne identification est de 81 %. Dans la deuxi??me solution, nous adoptons une strat??gie vectorielle pour appliquer la HMT directement sur les images multispectrales. La taille des ES de cette transformation morphologique est d??finie en utilisant la transformation dite chapeau haut-de-forme par reconstruction. Une ??tape de post-traitement inclut le filtrage de la v??g??tation par l???indice de la v??g??tation NDVI et la validation de la localisation des b??timents par l???information d???ombre. La m??thode est appliqu??e sur un espace urbain de type r??sidentiel. Des extraits d???images provenant des capteurs satellitaires Ikonos, GeoEye et WorldView 2 ont ??t?? trait??s. Le taux des b??timents reconnus est relativement ??lev?? pour tous les extraits - entre 85 % et 97 %. Le taux de bonne identification d??montre des r??sultats entre 74 % et 88 %. Les r??sultats obtenus nous permettent de conclure que les objectifs de ce travail de recherche, ?? savoir, la proposition d???une technique pour l???estimation de la similarit?? spectrale entre les pixels formant le toit d???un b??timent, l???int??gration de l???information multispectrale dans la HMT dans le but de d??tecter les b??timents, et la proposition d???une technique qui permet la d??finition semi-automatique des configurations b??timent/voisinage dans les images multispectrales, ont ??t?? atteints. // Abstract : Detection of buildings in very high spatial resolution images (THRS) has various practical applications and is recently a subject of intensive scientific research. It faces the complexity of the urban environment and the variety of image characteristics depending on the type of the sensor. The performance of existing building extraction methods is not yet sufficient to be generalized to a large scale (different urban patterns and sensors). Morphological operators have been proven effective for the detection of buildings in panchromatic (greyscale) very high spectral resolution (VHSR) images. The spectral information of multispectral images is jugged efficient to improve the results of the detection. The extension of morphological operators to multispectral images is not straightforward. As pixels of multispectral images are pixels vectors the components of which are the intensity values in the different bands, a strategy to order vectors must be adopted. This research thesis focuses on the application of the morphological transformation called Hit-or-Miss (HMT) on multispectral VHSR images in order to detect buildings. To address the issue of the extension of morphological operators to multispectral images we have proposed two solutions. The first one employs generation of greyscale images from multispectral bands, where potential buildings are enhanced. The grayscale HMT is then applied to these images in order to detect buildings. To enhance potential building locations we have proposed the use of Spectral Similarity Ratio (SSR). To avoid the need to set multiple configurations of structuring elements (SE) necessary for the implementation of the HMT, we have used fuzzy erosion and fuzzy dilation and examined the pixel response to different values of SE. The method has been tested on image subsets taken over residential areas. The average rate of recognition for the two sensors, Ikonos and GeoEye, is 85% and 80%, respectively. The average rate of correct identification is 85% and 84%, for Ikonos and GeoEye subsets, respectively. Having made some improvements, we then applied the method to large scenes from Ikonos and WorldView-2 images covering different urban patterns. The average rate of recognized buildings is 82%. The rate of correct identification is 81%. As a second solution, we have proposed a new vector based strategy which allows the multispectral information to be integrated into the percent occupancy HMT (POHMT). Thus, the POHMT has been directly applied on multispectral images. The parameters for the POHMT have been defined using the morphological transformation dubbed top hat by reconstruction. A post-processing step included filtering the vegetation and validating building locations by proximity to shadow. The method has been applied to urban residential areas. Image subsets from Ikonos, GeoEye and WorldView2 have been processed. The rate of recognized buildings is relatively high for all subsets - between 85% and 97%. The rate of correct identification is between 74 % and 88 %. The results allow us to conclude that the objectives of this research, namely, suggesting a technique for estimating the spectral similarity between the pixels forming the roof of a building, the integration of multispectral information in the HMT in order to detect buildings and the proposition of a semiautomatic technique for the definition of the configurations building/neighbourhood in multispectral images, have been achieved.